Spatial distribution pattern and economic value map of five species, walnut, plum, cornelian cherry, hawthorn, and medlar in Arasbaran protected area

Document Type : Complete scientific research article

Authors

1 Department of Forestry, Ahar Faculty of Agriculture and Natural resources, University of Tabriz

2 Department of forestry, university of Tehran

3 University of Yazd

4 University of tehran

Abstract

Background and objectives: The spatial distribution pattern of trees is one of the most important ecological features of forest communities that results from environmental heterogeneity, natural or human disturbance, interspecific and intraspecific competition, and impact of previous life. It reduces and adopts harvest costs and focuses on special distribution areas. It can be used to investigate the effect silvicultural interactions on stand, designing appropriate management plans, describing ecosystem sustainability, and reforestation activities. Low researches have been done about the spatial distribution pattern and economic value map of these products. Therefore, the purpose of this research is to investigate the spatial distribution pattern and map the economic value of five important species of forest trees, walnut (Juglans regia), plum (Prunus sp.), cornelian cherry (Cornus mas), hawthorn (Cratagus sp.), medlar (Mespilus germanica) in the Arasbaran protected area.

Materials and methods: Data were collected using full calipering inventory method at 140 hectares. In this method, spatial position of all fruit providing species was recorded. Because of high number of trees, recoding data by GPS for each tree decreases the data accuracy. Therefore, we used the distance and azimuth method. Then, we converted to the Cartesian system. All of these trees had a geographic position. Using forest type map of forest area, the distribution of trees in the region and number of each species in different types were investigated in order to determine the dominant type of presence of each species. In addition, the spaital distriubution pattern of trees was investigated by L function in ProgramitaJulio 2006. L function considers distance between trees of different species or the same species and it compute with Monte Carlo test. In order to provide a map of the distribution of economic value per hectare, the value of each species per ha was estimated by multiplying of the price per kilogram in yield per hectare and its map was depicted.

Results: The results showed that 10 species of fruit providing species were at the study area. Cornelian cherry (827 trees) and plum (421 trees) had highest frequency and pomegranate (32 trees) and barberry (16 trees) had the lowest frequency at the study area. Walnut, pear, plum, hawthorn, apple and pomegranate species were found in the Acer-Fraxino-Quercetum forest type. Cornelian cherry, barberry, hazelnut, and medlar were found at the Carpino- Quercetum. In general, the spatial distribution pattern of three species of plum, walnut and cornelian cherry was clumped. Medlar and hawthorn species had clumped distribution and at shorter distances, they had random and uniform distribution. The results showed that the lowest and the highest economic value per hectare was belonged to medlar with 900 Rials per hectare and walnut with 10343 thousand Rials per hectare. The economic value per hectare of walnut species varied from 809 to 10343 thousand rials.

Conclusion: The clumped distribution patterns of trees increases the economic value per ha. High economic value of trees increases the amount of fruit harvest at a short time and decreases the harvest costs. The economic value map of species can reduce harvest costs and also increase the management focus for management plans. Also, it makes key decisions for regulating conservation laws and discussions in these areas.

Keywords

Main Subjects


1. Akhavan, R., Sagheb Talebi, Kh., Hosseini, M., and Parhizagar, P. 2009. Investigation of
spatial pattern of trees during forest development stages in intact Fagus orientalis masses in
Kelardasht. Iranian J. Forest and Poplar Research, 18: 332-336. (In Persian)
2. Alavi, J., Zahedi Amiri, Gh., Noori, Z., and Marvi Mohajer, M.R. 2013. Application of
Ripley’s K-Function in Detecting Spatial Pattern of Wych Elm Species in Khayroud Forests,
North of Iran. Journal of Forest and Wood Science and Technology Research, 20(4): 21-39.
(In Persian)
3. Alijani, V., and Feghhi, J. 2011. Investigation on the Elm (Ulmus glabra Hudson) Spatial
Structure to Apply for Sustainable Management (Case Study: Gorazbon district, Kheirud
Forest). Journal of Environmental Studies, 60: 35-44. (In Persian)
4. Erfanifard, S.Y., and Mahdian, F. 2013. Comparative investigation on the methods of true
spatial pattern analysis of trees in forests, Case study: Wild pistachio research forest, Fars
province, Iran. Iranian Journal of Forest and Poplar Research, 20: 62-73. (In Persian)
5. Erfanifard, S.Y., Feghhi, J., Zobeiri, M., and Namiranian, M. 2009. Investigation of spatial
pattern of trees in Zagros forests. Iranian J. Natural Resources., 60: 1319-1328. (In Persian)
6. Ghanbari, S. 2015. Values, Capabilities and Socio-economic Constraints of Non-Wood
Forest Products in Arasbaran Forests, PhD Thesis. Faculty of Natural Resources, University
of Tehran. P330. (In Persian)
7. Hou, J.H., Mi, X.C., Liu, C.R., and Ma, K.P. 2004. Spatial patterns and associations in a
Quercus- Betula forest in northern China. J. Vegetation Sci., 15: 407-414.
8. Karimi, M., Pormajidian, M.R., Jalilvand, H., and Safari, A. 2012. Preliminary study for
application of O-ring function in determination of small-scale spatial pattern and interaction
species (Case study: Bayangan forests, Kermanshah). Iranian J. Forest and Poplar Res., 20:
608-621. (In Persian)
9. Kint, V., Robert, D.W., and Noel, L. 2004. Evaluation of sampling methods for estimation of
structural indices in forest stands. Ecological Modeling, 180: 461-476.
10. Linares-Palomino, R. 2005. Spatial distribution patterns of trees in a seasonally dry forest in
the Cerros de Amotape National Park, northwestern Peru. Peruvian J. Biol., 12(2): 317-326.
11. Modabberi, A., Susani, J., Abrari Vajari, K., Khosravi, Sh., and Farhadi, P. 2017.
Investigation of the structure of middle Zagros forests. Quarterly Journal of Forest Strategy,
1(3): 34-45. (In Persian)
12. Naidoo, R., and Ricketts, T.H. 2006. Mapping the economic costs and benefits of
conservation. PLoS biology, 4(11): e360.
13. Pommerening, A., and Stoyan, D. 2008. Reconstructing spatial tree points from nearest
neighbor summary statistics measured in small subwindows. Cana. J. Forest Res., 38: 1110-
1122.
14. Saha, D., and Sundriyal, R. 2011. Utilization of non-timber forest products in humid tropics:
Implications for management and livelihood. Forest Policy and Economics, 14(1): 28-40.
15. Salas, C., Le May, V., Nunez, P., Pacheco, P., and Espinosa, A. 2006. Spatial patterns in an
old-growth Nothofagus obliqua forest in south-central Chile. Forest Ecology and
Management, 231: 38-46.
16. Schaafsma, M., Morse-Jones, S., Posen, P., Swetnam, R., Balmford, A., Bateman, I.,
Burgess, N.D., Chamshama, S., Fisher, B., and Green, R. 2012. Towards transferable
functions for extraction of Non-timber Forest Products: A case study on charcoal production
in Tanzania. Ecological Economics, 80: 48-62.
17. Schaafsma, M., Morse-Jones, S., Posen, P., Swetnam, R., Balmford, A., Bateman, I.,
Burgess, N.D., Chamshama, S., Fisher, B., and Freeman, T. 2014. The importance of local
forest benefits: Economic valuation of Non-Timber Forest Products in the Eastern Arc
Mountains in Tanzania. Global Environmental Change, 24: 295-305.
18. Shariati Najaf Abadi, H., Soltani, E., Saeidi, Z., and Gorjestani Zade, Sh. 2016. Study of
Spatial Distribution of the Hawthorn (Crataegus monogyna) Trees Attacked by Orchard
Ermine (Yponomeuta padella) in Bazoft Forests of Chaharmahal and Bakhtiari Province.
Applied Ecology., 14: 39-48. (In Persian)
19. Soares Filho, B.S., Sónia Maria, C.R., William Leles, S.C., Amanda Ribeiro, D.O., Isabella
D.S., Lorenzini, T., Elaine, L., Frank, M., Welisson Wendel, E.G., Danilo D.S.F., and
Hermann, O.R. 2017. Economic Valuation of Changes in the Amazon Forest Area Value
maps for Non Timber Forest Products (NTFPs). Centro de Sensoriamento Remoto/UFMG:
83.
20. Sohrabi, H. 2015. Spatial pattern of woody species in Chartagh forest reserve, Ardal. Iranian
Journal of Forest and Poplar Research. 22: 27-38. (In Persian)
21. Srivastava, V., and Anitha, D. 2010. Mapping of non-timber forest products using remote
sensing and GIS. Tropical Ecology, 51(1): 107.
22. Vedel-Sørensen, M., Tovaranonte, J., Bøcher, P.K., Balslev, H., and Barfod, A.S. 2013.
Spatial distribution and environmental preferences of 10 economically important forest
palms in western South America. Forest Ecology and Management, 307: 284-292.
23. Zhang, Y.T., Li, J.M., Chang, Sh.L., Li, X., and Lu, J.J. 2012. Spatial distribution pattern of
Picea schrenkiana population in the Middle Tianshan Mountains and the relationship with
topographic attributes. Journal of Arid Land, 4(4): 457-468.
24. Zenner, E.K., and Peck, J.E. 2009. Characterizing structural conditions in mature managed
red pine: spatial dependency of metrics and adequacy of plot size. Forest Ecology and
Management, 257: 311-320.